{"id":"W1484959749","doi":"10.1111/j.0040-747x.2004.t01-1-00296.x","title":"<i>MUTUAL SPECIALISATION, SEAPORTS AND THE GEOGRAPHY OF AUTOMOBILE IMPORTS</i>","year":2004,"lang":"en","type":"article","venue":"Tijdschrift voor Economische en Sociale Geografie","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of California Transportation Center; National Science Foundation","keywords":"Port (circuit theory); Space (punctuation); Economic geography; Process (computing); Perspective (graphical); Business; Industrial organization; International trade; Regional science; Transport engineering; Economics; Geography; Computer science; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005173211,0.0001062583,0.0002570522,0.002086595,0.0007119774,0.003525448,0.0002521651,0.0003455272,0.004802491],"category_scores_gemma":[0.001952406,0.0001404678,0.0003070701,0.004691434,0.004273119,0.002182441,0.00289901,0.0003519185,0.000203629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001373996,"about_ca_system_score_gemma":0.0005262232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006992288,"about_ca_topic_score_gemma":0.007275946,"domain_scores_codex":[0.9994835,0.0002271686,0.00003099014,0.00007030124,0.0000931644,0.00009487559],"domain_scores_gemma":[0.9975574,0.0007826061,0.001174435,0.0001515079,0.0001880377,0.0001459602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001754803,0.00004771444,0.5894584,0.0002854576,0.0001887031,0.001335524,0.01597625,0.00749405,0.002398208,0.3511111,0.00159902,0.02993],"study_design_scores_gemma":[0.00001724995,0.0000998589,0.8240086,0.0002380703,0.0001119445,0.001788827,0.04530174,0.002817204,0.00105453,0.09039477,0.03412471,0.00004238466],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9745625,0.00100224,0.001490583,0.0009254792,0.000004987068,0.000004852597,0.0001114037,0.00001168079,0.02188635],"genre_scores_gemma":[0.9993154,0.0001912349,0.0001169722,0.000009482775,0.00000564314,0.000001745967,0.00002777741,0.000001746217,0.0003300787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006992288,"threshold_uncertainty_score":0.01606596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003335659741892464,"score_gpt":0.1753487058398266,"score_spread":0.1720130460979342,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}